Contrast-Enhanced Spectral Mammography and tumor size assessment: a valuable tool for appropriate surgical management of breast lesions

Nicosia, Luca; Bozzini, Anna Carla; Palma, Simone; Montesano, Marta; Signorelli, Giulia; Pesapane, Filippo; Latronico, Antuono; Bagnardi, Vincenzo; Frassoni, Samuele; Sangalli, Claudia; Farina, Mariagiorgia; Cassano, Enrico

doi:10.1007/s11547-022-01561-x

Cited by 11 publications

(10 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many studies confirmed the usefulness of CESM in clinical practice, as well as the usefulness of this relatively new diagnostic method [ 8 , 21 , 22 , 23 ]. CESM appears to offer similar diagnostic performance to MRI with the advantage of being cheaper, faster and applicable to more patients (e.g., patients with claustrophobia and pacemakers) [ 24 ].…”

Section: Discussionmentioning

confidence: 92%

Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner

Nicosia

Bozzini

Ballerini

et al. 2022

IJMS

Self Cite

View full text Add to dashboard Cite

We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with neoplastic breast lesions who underwent CESM before a biopsy and surgical assessment between January 2013 and February 2022. Radiomic analysis was performed on regions of interest selected from recombined CESM images. The association between the features and each evaluated endpoint (ER, PR, Ki-67, HER2+, triple negative, G2–G3 expressions) was investigated through univariate logistic regression. Among the significant and highly correlated radiomic features, we selected only the one most associated with the endpoint. From a group of 321 patients, we enrolled 205 malignant breast lesions. The median age at the exam was 50 years (interquartile range (IQR) 45–58). NGLDM_Contrast was the only feature that was positively associated with both ER and PR expression (p-values = 0.01). NGLDM_Coarseness was negatively associated with Ki-67 expression (p-value = 0.02). Five features SHAPE Volume(mL), SHAPE_Volume(vx), GLRLM_RLNU, NGLDM_Busyness and GLZLM_GLNU were all positively and significantly associated with HER2+; however, all of them were highly correlated. Radiomic features of CESM images could be helpful to predict particular molecular subtypes before a biopsy.

show abstract

Section: Discussionmentioning

confidence: 92%

Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner

Nicosia

Bozzini

Ballerini

et al. 2022

IJMS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Concordant with other studies, we showed CEM provided an accurate depiction of maximum tumour size compared to LEM, using size at histopathology as the gold standard. 19,24 Superior performance of CEM compared to LEM was identified regardless of breast density and in cases with minimal and mild BPE. No statistically significant difference in tumour size measurements was observed between LEM, CEM and surgical specimen in cases with moderate and marked BPE.…”

Section: Discussionmentioning

confidence: 96%

“…MRI is limited by lower availability, high cost, longer scan time, poorer patient tolerance and reduced specificity. 19 False-positive findings may translate to additional unnecessary biopsies, increased patient anxiety and potentially treatment delay. Our study adds to the growing body of literature regarding the utility of CEM in preoperative breast cancer staging.…”

Section: Discussionmentioning

confidence: 99%

Performance of contrast‐enhanced mammography for detecting multifocal and multicentric breast cancer and evaluating tumour size, and implications for surgical management: Early experience in a tertiary centre

Thanh Ha Nguyen,

Varma,

Lan Cheong Wah

et al. 2023

J Med Imag Rad Onc

View full text Add to dashboard Cite

IntroductionTo compare diagnostic accuracy of contrast‐enhanced mammography (CEM) with standard 2D digital mammography (equivalent to low‐energy image; LEM) for detection of multifocal and multicentric breast cancer and evaluation of tumour size and disease extent for preoperative planning.MethodsBiopsy proven breast cancer patients who underwent CEM preoperatively between January 2021 and January 2023 were included in this study. CEM and LEM images were independently reviewed by at least two blinded readers. Lesion location, number, size (maximal diameter) and extension across the midline and/or nipple invasion were recorded. Tumour number and size estimated on imaging were compared with final operative histology, which served as the gold standard.ResultsForty‐nine patients (48 females and 1 male) and 50 cases (one patient had bilateral breast lesions) were included in the analysis. Median patient age was 60 (IQR 51, 69). CEM had significantly higher lesion detection rate compared with LEM, with sensitivities of 78% for LEM and 92% for CEM for the index tumour and 15% for LEM and 100% for CEM for multicentric and multifocal cancer. We found no statistically significant difference in median tumour size measurements on CEM and final surgical specimen (P value = 0.97); however, a significant difference was identified in the tumour size measured on LEM and surgical specimen (P value < 0.001).ConclusionCEM is superior to standard 2D digital mammography for detection of multifocal and multicentric breast cancer and is a reliable and more accurate method for estimating tumour size.

show abstract

“…Dynamic contrast-enhanced (DCE) MRI and contrast-enhanced spectral mammography (CESM) offer the advantage of adding a functional evaluation to the morphological data through the administration of contrast medium that exploits neo-angiogenesis occurring in tumoral lesions [ 31 , 32 , 33 , 34 ]. Nowadays, MRI is accepted as the most sensitive imaging technique for detecting and staging breast cancer and is of great help in the study of particularly complex breasts, or of patients with an elevated hereditary–familial risk of developing breast cancer [ 35 ].…”

Section: Strengths and Limitations Of Current Breast Imaging Techniquesmentioning

confidence: 99%

How Radiomics Can Improve Breast Cancer Diagnosis and Treatment

Pesapane

Marco

Rapino

et al. 2023

JCM

Self Cite

View full text Add to dashboard Cite

Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases, and prognostication of treatment response and probability of recurrence. Radiomics is a quantitative approach to medical imaging, which aims to enhance the existing data available to clinicians by means of advanced mathematical analysis using artificial intelligence. Various published studies from different fields in imaging have highlighted the potential of radiomics to enhance clinical decision making. In this review, we describe the evolution of AI in breast imaging and its frontiers, focusing on handcrafted and deep learning radiomics. We present a typical workflow of a radiomics analysis and a practical “how-to” guide. Finally, we summarize the methodology and implementation of radiomics in breast cancer, based on the most recent scientific literature to help researchers and clinicians gain fundamental knowledge of this emerging technology. Alongside this, we discuss the current limitations of radiomics and challenges of integration into clinical practice with conceptual consistency, data curation, technical reproducibility, adequate accuracy, and clinical translation. The incorporation of radiomics with clinical, histopathological, and genomic information will enable physicians to move forward to a higher level of personalized management of patients with breast cancer.

show abstract

Contrast-Enhanced Spectral Mammography and tumor size assessment: a valuable tool for appropriate surgical management of breast lesions

Cited by 11 publications

References 18 publications

Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner

Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner

Performance of contrast‐enhanced mammography for detecting multifocal and multicentric breast cancer and evaluating tumour size, and implications for surgical management: Early experience in a tertiary centre

How Radiomics Can Improve Breast Cancer Diagnosis and Treatment

Contact Info

Product

Resources

About